2017
DOI: 10.1007/s11241-017-9283-6
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Designing end-to-end resource reservations in predictable distributed embedded systems

Abstract: Contemporary distributed embedded systems in many domains have become highly complex due to ever-increasing demand on advanced computer controlled functionality. The resource reservation techniques can be effective in lowering the software complexity, ensuring predictability and allowing flexibility during the development and execution of these systems. This paper proposes a novel end-to-end resource reservation model for distributed embedded systems. In order to support the development of predictable systems … Show more

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Cited by 12 publications
(6 citation statements)
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References 28 publications
(35 reference statements)
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“…e service platform is composed of distributed servers, provides computer and network services for data storage and distribution, provides cloud preprocessing services, and provides analysis and feedback of local smart cards and other service terminal devices [23]. Its purpose is to reduce bandwidth pressure, reduce application delays, and reduce the computing load of the data center [24]. e fog computing framework is shown in Figure 1.…”
Section: Bayesian Algorithm Of Simulation Interactive Credibilitymentioning
confidence: 99%
“…e service platform is composed of distributed servers, provides computer and network services for data storage and distribution, provides cloud preprocessing services, and provides analysis and feedback of local smart cards and other service terminal devices [23]. Its purpose is to reduce bandwidth pressure, reduce application delays, and reduce the computing load of the data center [24]. e fog computing framework is shown in Figure 1.…”
Section: Bayesian Algorithm Of Simulation Interactive Credibilitymentioning
confidence: 99%
“…Compared with TTW, which tightly couples tasks and messages by co-scheduling them, DRP incurs significantly higher worst-case delays, and is thus not suitable for demanding CPS applications [3] In the wired domain, a lot of work has been done on time-triggered architectures, such as the Time-Triggered Protocol (TTP) [30], the static-segment of FlexRay [15], or Time-Triggered Ethernet [28]. Like TTW, many recent works in this area also use SMT or MILP based methods to synthesize and/or analyze static (co-)schedules for those architectures [39,12,5,41,44]. The key difference to TTW, however, is that these approaches assume that a message can be scheduled at any point in time: while it is a perfectly valid hypothesis for a wired system, this assumption is not compatible with the use of communication rounds in a 23:5 wireless setting.…”
Section: Related Workmentioning
confidence: 99%
“…Ultimately, (C1) and (C2) can be formulated as ILP constraints using ( 8), (9), and the following two equations:…”
Section: Algorithm 1 Pseudo-code Of the Schedule Synthesismentioning
confidence: 99%
“…In the wired domain, much work has been done on time-triggered architecture, like TTP [18], the static-segment of FlexRay [19], or TTEthernet [20]. Many recent works use SMT-of ILP-based methods to synthesize and/or analyze static (co-)schedules for those architectures [8], [9], [12], [21], [22]. However, these approaches assume that a message can be scheduled at anytime.…”
Section: Related Workmentioning
confidence: 99%
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